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Virtual environment for the design of position trajectory tracking controllers of remotely operated vehicles
Author(s) -
David Javier Muñoz-Aldana,
Carlos Alberto Gaviria-López
Publication year - 2019
Publication title -
iteckne
Language(s) - English
Resource type - Journals
eISSN - 2339-3483
pISSN - 1692-1798
DOI - 10.15332/iteckne.v16i2.2358
Subject(s) - matlab , trajectory , remotely operated underwater vehicle , computer science , control engineering , linear quadratic regulator , position (finance) , robotics , underwater , virtual machine , simulation , controller (irrigation) , control (management) , engineering , robot , artificial intelligence , mobile robot , agronomy , oceanography , physics , finance , astronomy , economics , biology , geology , operating system
This article presents a virtual environment based on co-simulation between MatLab and MSC Adams, allowing simulation, analysis, development and validation of control strategies for tracking of position trajectories of a Remotely Operated Vehicle (ROV). The simulation results in the horizontal plane show that it is possible, in an uncomplicated way, to construct a virtual environment, which allows observing realistic movements when the forces exerted on an ROV are provided. Taking advantage of the properties of co-simulation, the experiences in this work show that this simulation strategy is very suitable for analysis purposes and control design, allowing researchers and professionals the wide use of control tools available in MATLAB for this end. In this work, a robust linear quadratic regulator (LQR) with integral action has been used to evaluate the performance of the proposed virtual environment for tracking of position trajectories. To validation purposes, widely used trajectories in naval study designs were employed such as the Zig -Zag shaped and the Circular shaped trajectories. Simulation results show that the integration of both, MatLab and MSC Adams, effectively addressees the problem of evaluation of performance of control strategies in the virtual environment. The presented approach allows gaining experience about the challenges of this kind of control problems, before dealing with the complex aspects of tuning in real experimental environments, avoiding losses and cost overruns for underwater robotics projects.

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